With the advancement of technology, multi-domain ‘mechatronics’ systems are being developed that operates in a closed-loop/close-interaction. Examples of such system include vehicle systems, aircraft systems, automotive systems, turbine engines, and so on. Since the systems being developed these days are complex, the health management of such systems pose challenges, as failure of any critical system component can trigger catastrophic system failures. Hence, health management of such multi-domain complex systems is of vital importance.
An effective health management of these complex systems requires monitoring of all components of the system. The conventional systems for health management of these complex systems use sensor based approach where distinct sensors are deployed for monitoring individual component or subsystem. Additionally or alternatively, conventional health management systems follow condition based maintenance or offline big data analytics which is not real time and predominantly not on-board. Such technologies leverage on sensory data as a source and also are tightly coupled to subsystem level.
The inventors here have recognized several technical problems with such conventional systems, as explained below. In a complex system, sensor count increases as the system becomes more complex, thereby loading the conventional health management system with more elements to monitor. In addition, the conventional health management system provides a purely hardware based approach and hence, it is difficult to meet real time constraints set by a hard real-time complex system.